A new approach to parallel joint diagonalization of symmetric matrices
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A new algorithm for parallel joint diagonalization of symmetric (Hermitian) matrices is introduced. The approach is based on the Jacobi diagonalization, utilizes the distribution of the computational power and memory space and runs on a heterogeneous personal computer systems with an arbitrary number of processing units. Its basic performance indices are outlined and its application to the blind source separation problem is discussed.
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